Package weka.attributeSelection
Class RaceSearch
- java.lang.Object
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- weka.attributeSelection.ASSearch
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- weka.attributeSelection.RaceSearch
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- All Implemented Interfaces:
java.io.Serializable
,RankedOutputSearch
,OptionHandler
,RevisionHandler
,TechnicalInformationHandler
public class RaceSearch extends ASSearch implements RankedOutputSearch, OptionHandler, TechnicalInformationHandler
Races the cross validation error of competing attribute subsets. Use in conjuction with a ClassifierSubsetEval. RaceSearch has four modes:
forward selection races all single attribute additions to a base set (initially no attributes), selects the winner to become the new base set and then iterates until there is no improvement over the base set.
Backward elimination is similar but the initial base set has all attributes included and races all single attribute deletions.
Schemata search is a bit different. Each iteration a series of races are run in parallel. Each race in a set determines whether a particular attribute should be included or not---ie the race is between the attribute being "in" or "out". The other attributes for this race are included or excluded randomly at each point in the evaluation. As soon as one race has a clear winner (ie it has been decided whether a particular attribute should be inor not) then the next set of races begins, using the result of the winning race from the previous iteration as new base set.
Rank race first ranks the attributes using an attribute evaluator and then races the ranking. The race includes no attributes, the top ranked attribute, the top two attributes, the top three attributes, etc.
It is also possible to generate a raked list of attributes through the forward racing process. If generateRanking is set to true then a complete forward race will be run---that is, racing continues until all attributes have been selected. The order that they are added in determines a complete ranking of all the attributes.
Racing uses paired and unpaired t-tests on cross-validation errors of competing subsets. When there is a significant difference between the means of the errors of two competing subsets then the poorer of the two can be eliminated from the race. Similarly, if there is no significant difference between the mean errors of two competing subsets and they are within some threshold of each other, then one can be eliminated from the race.
For more information see:
Andrew W. Moore, Mary S. Lee: Efficient Algorithms for Minimizing Cross Validation Error. In: Eleventh International Conference on Machine Learning, 190-198, 1994. BibTeX:@inproceedings{Moore1994, author = {Andrew W. Moore and Mary S. Lee}, booktitle = {Eleventh International Conference on Machine Learning}, pages = {190-198}, publisher = {Morgan Kaufmann}, title = {Efficient Algorithms for Minimizing Cross Validation Error}, year = {1994} }
Valid options are:-R <0 = forward | 1 = backward race | 2 = schemata | 3 = rank> Type of race to perform. (default = 0).
-L <significance> Significance level for comaparisons (default = 0.001(forward/backward/rank)/0.01(schemata)).
-T <threshold> Threshold for error comparison. (default = 0.001).
-A <attribute evaluator> Attribute ranker to use if doing a rank search. Place any evaluator options LAST on the command line following a "--". eg. -A weka.attributeSelection.GainRatioAttributeEval ... -- -M. (default = GainRatioAttributeEval)
-F <0 = 10 fold | 1 = leave-one-out> Folds for cross validation (default = 0 (1 if schemata race)
-Q Generate a ranked list of attributes. Forces the search to be forward and races until all attributes have selected, thus producing a ranking.
-N <num to select> Specify number of attributes to retain from the ranking. Overides -T. Use in conjunction with -Q
-J <threshold> Specify a theshold by which attributes may be discarded from the ranking. Use in conjuction with -Q
-Z Verbose output for monitoring the search.
Options specific to evaluator weka.attributeSelection.GainRatioAttributeEval:
-M treat missing values as a seperate value.
- Version:
- $Revision: 1.26 $
- Author:
- Mark Hall (mhall@cs.waikato.ac.nz)
- See Also:
- Serialized Form
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Field Summary
Fields Modifier and Type Field Description static Tag[]
TAGS_SELECTION
static Tag[]
XVALTAGS_SELECTION
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Constructor Summary
Constructors Constructor Description RaceSearch()
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description java.lang.String
attributeEvaluatorTipText()
Returns the tip text for this propertyjava.lang.String
debugTipText()
Returns the tip text for this propertyjava.lang.String
foldsTypeTipText()
Returns the tip text for this propertyjava.lang.String
generateRankingTipText()
Returns the tip text for this propertyASEvaluation
getAttributeEvaluator()
Get the attribute evaluator used to generate the ranking.int
getCalculatedNumToSelect()
Gets the calculated number of attributes to retain.boolean
getDebug()
Get whether output is to be verboseSelectedTag
getFoldsType()
Get the xfold typeboolean
getGenerateRanking()
Gets whether ranking has been requested.int
getNumToSelect()
Gets the number of attributes to be retained.java.lang.String[]
getOptions()
Gets the current settings of BestFirst.SelectedTag
getRaceType()
Get the race typejava.lang.String
getRevision()
Returns the revision string.double
getSelectionThreshold()
Returns the threshold so that the AttributeSelection module can discard attributes from the ranking.double
getSignificanceLevel()
Get the significance levelTechnicalInformation
getTechnicalInformation()
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.double
getThreshold()
Get the thresholdjava.lang.String
globalInfo()
Returns a string describing this search methodjava.util.Enumeration
listOptions()
Returns an enumeration describing the available options.java.lang.String
numToSelectTipText()
Returns the tip text for this propertyjava.lang.String
raceTypeTipText()
Returns the tip text for this propertydouble[][]
rankedAttributes()
Returns a X by 2 list of attribute indexes and corresponding evaluations from best (highest) to worst.int[]
search(ASEvaluation ASEval, Instances data)
Searches the attribute subset space by racing cross validation errors of competing subsetsjava.lang.String
selectionThresholdTipText()
Returns the tip text for this propertyvoid
setAttributeEvaluator(ASEvaluation newEvaluator)
Set the attribute evaluator to use for generating the ranking.void
setDebug(boolean d)
Set whether verbose output should be generated.void
setFoldsType(SelectedTag d)
Set the xfold typevoid
setGenerateRanking(boolean doRank)
Records whether the user has requested a ranked list of attributes.void
setNumToSelect(int n)
Specify the number of attributes to select from the ranked list (if generating a ranking).void
setOptions(java.lang.String[] options)
Parses a given list of options.void
setRaceType(SelectedTag d)
Set the race typevoid
setSelectionThreshold(double threshold)
Set the threshold by which the AttributeSelection module can discard attributes.void
setSignificanceLevel(double sig)
Sets the significance level to usevoid
setThreshold(double t)
Sets the threshold for comparisonsjava.lang.String
significanceLevelTipText()
Returns the tip text for this propertyjava.lang.String
thresholdTipText()
Returns the tip text for this propertyjava.lang.String
toString()
Returns a string represenation-
Methods inherited from class weka.attributeSelection.ASSearch
forName, makeCopies
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Method Detail
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globalInfo
public java.lang.String globalInfo()
Returns a string describing this search method- Returns:
- a description of the search method suitable for displaying in the explorer/experimenter gui
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getTechnicalInformation
public TechnicalInformation getTechnicalInformation()
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.- Specified by:
getTechnicalInformation
in interfaceTechnicalInformationHandler
- Returns:
- the technical information about this class
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raceTypeTipText
public java.lang.String raceTypeTipText()
Returns the tip text for this property- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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setRaceType
public void setRaceType(SelectedTag d)
Set the race type- Parameters:
d
- the type of race
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getRaceType
public SelectedTag getRaceType()
Get the race type- Returns:
- the type of race
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significanceLevelTipText
public java.lang.String significanceLevelTipText()
Returns the tip text for this property- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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setSignificanceLevel
public void setSignificanceLevel(double sig)
Sets the significance level to use- Parameters:
sig
- the significance level
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getSignificanceLevel
public double getSignificanceLevel()
Get the significance level- Returns:
- the current significance level
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thresholdTipText
public java.lang.String thresholdTipText()
Returns the tip text for this property- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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setThreshold
public void setThreshold(double t)
Sets the threshold for comparisons- Specified by:
setThreshold
in interfaceRankedOutputSearch
- Parameters:
t
- the threshold to use
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getThreshold
public double getThreshold()
Get the threshold- Specified by:
getThreshold
in interfaceRankedOutputSearch
- Returns:
- the current threshold
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foldsTypeTipText
public java.lang.String foldsTypeTipText()
Returns the tip text for this property- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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setFoldsType
public void setFoldsType(SelectedTag d)
Set the xfold type- Parameters:
d
- the type of xval
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getFoldsType
public SelectedTag getFoldsType()
Get the xfold type- Returns:
- the type of xval
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debugTipText
public java.lang.String debugTipText()
Returns the tip text for this property- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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setDebug
public void setDebug(boolean d)
Set whether verbose output should be generated.- Parameters:
d
- true if output is to be verbose.
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getDebug
public boolean getDebug()
Get whether output is to be verbose- Returns:
- true if output will be verbose
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attributeEvaluatorTipText
public java.lang.String attributeEvaluatorTipText()
Returns the tip text for this property- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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setAttributeEvaluator
public void setAttributeEvaluator(ASEvaluation newEvaluator)
Set the attribute evaluator to use for generating the ranking.- Parameters:
newEvaluator
- the attribute evaluator to use.
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getAttributeEvaluator
public ASEvaluation getAttributeEvaluator()
Get the attribute evaluator used to generate the ranking.- Returns:
- the evaluator used to generate the ranking.
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generateRankingTipText
public java.lang.String generateRankingTipText()
Returns the tip text for this property- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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setGenerateRanking
public void setGenerateRanking(boolean doRank)
Records whether the user has requested a ranked list of attributes.- Specified by:
setGenerateRanking
in interfaceRankedOutputSearch
- Parameters:
doRank
- true if ranking is requested
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getGenerateRanking
public boolean getGenerateRanking()
Gets whether ranking has been requested. This is used by the AttributeSelection module to determine if rankedAttributes() should be called.- Specified by:
getGenerateRanking
in interfaceRankedOutputSearch
- Returns:
- true if ranking has been requested.
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numToSelectTipText
public java.lang.String numToSelectTipText()
Returns the tip text for this property- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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setNumToSelect
public void setNumToSelect(int n)
Specify the number of attributes to select from the ranked list (if generating a ranking). -1 indicates that all attributes are to be retained.- Specified by:
setNumToSelect
in interfaceRankedOutputSearch
- Parameters:
n
- the number of attributes to retain
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getNumToSelect
public int getNumToSelect()
Gets the number of attributes to be retained.- Specified by:
getNumToSelect
in interfaceRankedOutputSearch
- Returns:
- the number of attributes to retain
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getCalculatedNumToSelect
public int getCalculatedNumToSelect()
Gets the calculated number of attributes to retain. This is the actual number of attributes to retain. This is the same as getNumToSelect if the user specifies a number which is not less than zero. Otherwise it should be the number of attributes in the (potentially transformed) data.- Specified by:
getCalculatedNumToSelect
in interfaceRankedOutputSearch
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selectionThresholdTipText
public java.lang.String selectionThresholdTipText()
Returns the tip text for this property- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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setSelectionThreshold
public void setSelectionThreshold(double threshold)
Set the threshold by which the AttributeSelection module can discard attributes.- Parameters:
threshold
- the threshold.
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getSelectionThreshold
public double getSelectionThreshold()
Returns the threshold so that the AttributeSelection module can discard attributes from the ranking.
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listOptions
public java.util.Enumeration listOptions()
Returns an enumeration describing the available options.- Specified by:
listOptions
in interfaceOptionHandler
- Returns:
- an enumeration of all the available options.
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setOptions
public void setOptions(java.lang.String[] options) throws java.lang.Exception
Parses a given list of options. Valid options are:-R <0 = forward | 1 = backward race | 2 = schemata | 3 = rank> Type of race to perform. (default = 0).
-L <significance> Significance level for comaparisons (default = 0.001(forward/backward/rank)/0.01(schemata)).
-T <threshold> Threshold for error comparison. (default = 0.001).
-A <attribute evaluator> Attribute ranker to use if doing a rank search. Place any evaluator options LAST on the command line following a "--". eg. -A weka.attributeSelection.GainRatioAttributeEval ... -- -M. (default = GainRatioAttributeEval)
-F <0 = 10 fold | 1 = leave-one-out> Folds for cross validation (default = 0 (1 if schemata race)
-Q Generate a ranked list of attributes. Forces the search to be forward and races until all attributes have selected, thus producing a ranking.
-N <num to select> Specify number of attributes to retain from the ranking. Overides -T. Use in conjunction with -Q
-J <threshold> Specify a theshold by which attributes may be discarded from the ranking. Use in conjuction with -Q
-Z Verbose output for monitoring the search.
Options specific to evaluator weka.attributeSelection.GainRatioAttributeEval:
-M treat missing values as a seperate value.
- Specified by:
setOptions
in interfaceOptionHandler
- Parameters:
options
- the list of options as an array of strings- Throws:
java.lang.Exception
- if an option is not supported
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getOptions
public java.lang.String[] getOptions()
Gets the current settings of BestFirst.- Specified by:
getOptions
in interfaceOptionHandler
- Returns:
- an array of strings suitable for passing to setOptions()
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search
public int[] search(ASEvaluation ASEval, Instances data) throws java.lang.Exception
Searches the attribute subset space by racing cross validation errors of competing subsets
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rankedAttributes
public double[][] rankedAttributes() throws java.lang.Exception
Description copied from interface:RankedOutputSearch
Returns a X by 2 list of attribute indexes and corresponding evaluations from best (highest) to worst.- Specified by:
rankedAttributes
in interfaceRankedOutputSearch
- Returns:
- the ranked list of attribute indexes in an array of ints
- Throws:
java.lang.Exception
- if the ranking can't be produced
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toString
public java.lang.String toString()
Returns a string represenation- Overrides:
toString
in classjava.lang.Object
- Returns:
- a string representation
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getRevision
public java.lang.String getRevision()
Returns the revision string.- Specified by:
getRevision
in interfaceRevisionHandler
- Overrides:
getRevision
in classASSearch
- Returns:
- the revision
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